Genetic Loci Associated With Periodontitis: The <scp>FinnGen</scp> Study Based on National Health Registers
Bibliographic record
Abstract
AIM: To perform a genome-wide association study (GWAS) for periodontitis in the FinnGen cohort, as genetic factors contribute to periodontitis. MATERIALS AND METHODS: We included nearly 250,000 Finnish individuals who had visited a dentist in the public healthcare sector for a clinical oral examination. We designed three periodontitis phenotypes based on diagnosis and procedure codes and CPI indexes in national health registers. RESULTS: We identified 11 independent genetic loci associated with periodontitis, among which 6 were common and novel. A locus near the FST gene was associated with two phenotypes, whereas other lead SNPs were located near ARL15, MFHAS1, DEFB130A and APOE. Additionally, all phenotypes in the discovery and replication cohorts were associated with genetic variations in the HLA region. Furthermore, imputed HLA allele frequencies identified independent associations between HLA-DRB1, HLA-DPB1 and HLA-DQA1 and periodontitis. Based on single-cell RNA sequencing, the expression of genes near our lead SNPs across all three phenotypes was particularly enriched in gingival cell lineages important in the pathogenesis of periodontitis. Phenotypical and genetic correlations revealed associations between periodontitis and bacterial diseases, as well as autoimmune and cardiometabolic phenotypes. CONCLUSIONS: Our GWAS suggests that genetic variation contributing to immune dysregulation is involved in the pathogenesis of periodontitis, which has considerable genetic similarity with other complex traits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".